On 9/15/2010 10:50 AM, Shashi Kant wrote:
Shawn, I have done some research into this, machine-vision especially on a large scale is a hard problem, not to be entered into lightly. I would recommend starting with OpenCV - a comprehensive toolkit for extracting various features such as Color, Edge etc from images. Also there is a project LIRE http://www.semanticmetadata.net/lire/ which attempts to do something along what you are thinking of. Not sure how well it works.
Lire looks promising, but how hard is it to integrate the content-based search into Solr as opposed to Lucene? I myself am not a Java developer. I have access to people who are, but their time is scarce.
I use DIH to populate my index, so I would have to do analysis outside of Solr to populate the database. From there, I would come up with a new schema and DIH config to re-import either the entire index or just documents that have been recently updated. I have a build system to handle these things on all my shards.
OpenCV looks intimidating, but potentially very useful and for most things would probably not require custom code in Solr. To mention the most obvious capability I can find, I think many of our customers would love to be able to check a box to include or exclude photos with faces in them.
I can tell it's getting late ... I imagined a scenario similar to the Kohler commercial where a woman pulls out a faucet at an architect's office ... "Design a website around #00ebc9."
Thanks, Shawn
